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## A Semantic Knowledge Complementarity based Decoupling Framework for Semi-supervised Class-imbalanced Medical Image Segmentation (CVPR 2025)
Official code for "A Semantic Knowledge Complementarity based Decoupling Framework
for Semi-supervised Class-imbalanced Medical Image Segmentation". (CVPR 2025)
# Data Preparation

- The **Synapse** dataset can be downloaded from <https://www.synapse.org/#!Synapse:syn3193805/wiki/>.

Run ```preprocess.py``` to convert ```.nii.gz``` files into ```.npy```.

- The **AMOS** dataset can be downloaded from <https://amos22.grand-challenge.org/Dataset/>.

Run  ```preprocess_amos.py``` to convert ```.nii.gz``` files into ```.npy```.

- The format of the preprocessed data is ```.npy``` with a size of ```80×160×160```. We will upload the preprocessed data as soon as possible.

The preprocessed Synapse dataset has been uploaded to <https://pan.baidu.com/s/1TO9-PE4ZkjPMdw_QPIVSPQ?pwd=zae8>
  
- The data splits have been uploaded to the codebase.

# Training
When training on the Synapse dataset, we conducted 3 experiments with random seeds of ```0```,```1```,```666``` respectively. The other hyperparameters are as follows:

```
max_epoch=1500, cps_loss='w_ce+dice', sup_loss='w_ce+dice', batch_size=2, num_workers=2, base_lr=0.3, ema_w=0.99, cps_w=10, cps_rampup=True, consistency_rampup=None
```
When training on the AMOS dataset, we conducted 1 experiment with random seeds of ```0```. The other hyperparameters are as follows:
```
max_epoch=1500, cps_loss='w_ce+dice', sup_loss='w_ce+dice', batch_size=2, num_workers=2, base_lr=0.1, ema_w=0.99, cps_w=10, cps_rampup=True, consistency_rampup=None
```
Then run ```train_skcdf.py``` to train.
# Testing
Run ```test.py``` to generate prediction results.
# Evaluating
Run ```evaluate_Ntimes.py```  to calculate average Dice and ASD.

# Citation
If this code is useful for your research, please cite:
```bibtex
@inproceedings{zhang2025semantic,
  title={A Semantic Knowledge Complementarity based Decoupling Framework for Semi-supervised Class-imbalanced Medical Image Segmentation},
  author={Zhang, Zheng and Yin, Guanchun and Zhang, Bo and Liu, Wu and Zhou, Xiuzhuang and Wang, Wendong},
  booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference},
  pages={25940--25949},
  year={2025}
}
```
# Acknowledgements
This project is built upon the following outstanding open-source projects: [GenericSSL](https://github.com/xmed-lab/GenericSSL), [AllSpark](https://github.com/xmed-lab/AllSpark) and [ABC](https://github.com/LeeHyuck/ABC). We deeply appreciate their contributions to the community.

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